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The New AI: General & Sound & Relevant for Physics

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Book cover Artificial General Intelligence

Part of the book series: Cognitive Technologies ((COGTECH))

Summary

Most traditional artificial intelligence (AI) systems of the past 50 years are either very limited, or based on heuristics, or both. The new millennium, however, has brought substantial progress in the field of theoretically optimal and practically feasible algorithms for prediction, search, inductive inference based on Occam’s razor, problem solving, decision making, and reinforcement learning in environments of a very general type. Since inductive inference is at the heart of all inductive sciences, some of the results are relevant not only for AI and computer science but also for physics, provoking nontraditional predictions based on Zuse’s thesis of the computer-generated universe.

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Author information

Authors and Affiliations

  1. IDSIA, Galleria 2, 6928, Manno (Lugano), Switzerland

    Jürgen Schmidhuber

  2. TU Munich, Boltzmannstr. 3, 85748, Garching, München, Germany

    Jürgen Schmidhuber

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  1. Jürgen Schmidhuber
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Editors and Affiliations

  1. AGIRI — Artificial General Intelligence Research Institute, 1405 Bernerd Place, Rockville, MD, 20851, USA

    Ben Goertzel  & Cassio Pennachin  & 

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Schmidhuber, J. (2007). The New AI: General & Sound & Relevant for Physics. In: Goertzel, B., Pennachin, C. (eds) Artificial General Intelligence. Cognitive Technologies. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-68677-4_6

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  • DOI: https://doi.org/10.1007/978-3-540-68677-4_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23733-4

  • Online ISBN: 978-3-540-68677-4

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